Semantic Web search based on rough sets and Fuzzy Formal Concept Analysis

被引：75
|
作者：
Formica, Anna [1 ]
机构：
[1] CNR, Ist Anal Sistemi & Informat, I-00185 Rome, Italy
来源：
KNOWLEDGE-BASED SYSTEMS | 2012年 / 26卷
关键词：
Semantic Web; Formal Concept Analysis; Fuzzy information; Rough set theory; Formal concept; CONCEPT SIMILARITY; CONCEPT LATTICES; DESCRIPTION LOGICS;
D O I：
10.1016/j.knosys.2011.06.018
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Fuzzy Formal Concept Analysis (FFCA) is a generalization of Formal Concept Analysis (FCA) for modeling uncertainty information. FFCA provides a mathematical framework which can support the construction of formal ontologies in the presence of uncertainty data for the development of the Semantic Web. In this paper, we show how rough set theory can be employed in combination with FFCA to perform Semantic Web search and discovery of information in the Web. (C) 2011 Elsevier B.V. All rights reserved.
引用
收藏
页码：40 / 47
页数：8
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